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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Thu, 22 Dec 2016 21:00:26 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/22/t1482437731l9qf973beq2xmxt.htm/, Retrieved Fri, 01 Nov 2024 03:28:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302675, Retrieved Fri, 01 Nov 2024 03:28:59 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

114

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [(Partial) Autocorrelation Function] [ACF1] [2016-12-22 17:08:50] [267314984f6394bb93cd815224aa34ba]
- R  D    [(Partial) Autocorrelation Function] [acf5] [2016-12-22 20:00:26] [636d0f72197ac5e1dae4a755427db02a] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302675&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [ROW]

R Framework error message[/C][C]

Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302675&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302675&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.613519	-3.782	0.000268
2	0.194625	1.1997	0.118832
3	-0.092295	-0.5689	0.28637
4	0.171879	1.0595	0.148023
5	-0.288584	-1.779	0.041624
6	0.091503	0.5641	0.288012
7	0.120467	0.7426	0.231143
8	-0.11752	-0.7244	0.236616
9	0.040757	0.2512	0.40149
10	-0.014163	-0.0873	0.465442
11	0.23643	1.4574	0.076604
12	-0.424769	-2.6185	0.006308

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.613519 & -3.782 & 0.000268 \tabularnewline
2 & 0.194625 & 1.1997 & 0.118832 \tabularnewline
3 & -0.092295 & -0.5689 & 0.28637 \tabularnewline
4 & 0.171879 & 1.0595 & 0.148023 \tabularnewline
5 & -0.288584 & -1.779 & 0.041624 \tabularnewline
6 & 0.091503 & 0.5641 & 0.288012 \tabularnewline
7 & 0.120467 & 0.7426 & 0.231143 \tabularnewline
8 & -0.11752 & -0.7244 & 0.236616 \tabularnewline
9 & 0.040757 & 0.2512 & 0.40149 \tabularnewline
10 & -0.014163 & -0.0873 & 0.465442 \tabularnewline
11 & 0.23643 & 1.4574 & 0.076604 \tabularnewline
12 & -0.424769 & -2.6185 & 0.006308 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302675&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]-0.613519[/C][C]-3.782[/C][C]0.000268[/C][/ROW]
[ROW][C]2[/C][C]0.194625[/C][C]1.1997[/C][C]0.118832[/C][/ROW]
[ROW][C]3[/C][C]-0.092295[/C][C]-0.5689[/C][C]0.28637[/C][/ROW]
[ROW][C]4[/C][C]0.171879[/C][C]1.0595[/C][C]0.148023[/C][/ROW]
[ROW][C]5[/C][C]-0.288584[/C][C]-1.779[/C][C]0.041624[/C][/ROW]
[ROW][C]6[/C][C]0.091503[/C][C]0.5641[/C][C]0.288012[/C][/ROW]
[ROW][C]7[/C][C]0.120467[/C][C]0.7426[/C][C]0.231143[/C][/ROW]
[ROW][C]8[/C][C]-0.11752[/C][C]-0.7244[/C][C]0.236616[/C][/ROW]
[ROW][C]9[/C][C]0.040757[/C][C]0.2512[/C][C]0.40149[/C][/ROW]
[ROW][C]10[/C][C]-0.014163[/C][C]-0.0873[/C][C]0.465442[/C][/ROW]
[ROW][C]11[/C][C]0.23643[/C][C]1.4574[/C][C]0.076604[/C][/ROW]
[ROW][C]12[/C][C]-0.424769[/C][C]-2.6185[/C][C]0.006308[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302675&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302675&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.613519	-3.782	0.000268
2	0.194625	1.1997	0.118832
3	-0.092295	-0.5689	0.28637
4	0.171879	1.0595	0.148023
5	-0.288584	-1.779	0.041624
6	0.091503	0.5641	0.288012
7	0.120467	0.7426	0.231143
8	-0.11752	-0.7244	0.236616
9	0.040757	0.2512	0.40149
10	-0.014163	-0.0873	0.465442
11	0.23643	1.4574	0.076604
12	-0.424769	-2.6185	0.006308

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.613519	-3.782	0.000268
2	-0.291505	-1.797	0.040147
3	-0.204915	-1.2632	0.10711
4	0.102168	0.6298	0.266295
5	-0.180641	-1.1135	0.136234
6	-0.360207	-2.2205	0.016213
7	-0.067468	-0.4159	0.339912
8	-0.027854	-0.1717	0.43229
9	0.007649	0.0472	0.481319
10	-0.116092	-0.7156	0.239294
11	0.276605	1.7051	0.048169
12	-0.069242	-0.4268	0.335954

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.613519 & -3.782 & 0.000268 \tabularnewline
2 & -0.291505 & -1.797 & 0.040147 \tabularnewline
3 & -0.204915 & -1.2632 & 0.10711 \tabularnewline
4 & 0.102168 & 0.6298 & 0.266295 \tabularnewline
5 & -0.180641 & -1.1135 & 0.136234 \tabularnewline
6 & -0.360207 & -2.2205 & 0.016213 \tabularnewline
7 & -0.067468 & -0.4159 & 0.339912 \tabularnewline
8 & -0.027854 & -0.1717 & 0.43229 \tabularnewline
9 & 0.007649 & 0.0472 & 0.481319 \tabularnewline
10 & -0.116092 & -0.7156 & 0.239294 \tabularnewline
11 & 0.276605 & 1.7051 & 0.048169 \tabularnewline
12 & -0.069242 & -0.4268 & 0.335954 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302675&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]-0.613519[/C][C]-3.782[/C][C]0.000268[/C][/ROW]
[ROW][C]2[/C][C]-0.291505[/C][C]-1.797[/C][C]0.040147[/C][/ROW]
[ROW][C]3[/C][C]-0.204915[/C][C]-1.2632[/C][C]0.10711[/C][/ROW]
[ROW][C]4[/C][C]0.102168[/C][C]0.6298[/C][C]0.266295[/C][/ROW]
[ROW][C]5[/C][C]-0.180641[/C][C]-1.1135[/C][C]0.136234[/C][/ROW]
[ROW][C]6[/C][C]-0.360207[/C][C]-2.2205[/C][C]0.016213[/C][/ROW]
[ROW][C]7[/C][C]-0.067468[/C][C]-0.4159[/C][C]0.339912[/C][/ROW]
[ROW][C]8[/C][C]-0.027854[/C][C]-0.1717[/C][C]0.43229[/C][/ROW]
[ROW][C]9[/C][C]0.007649[/C][C]0.0472[/C][C]0.481319[/C][/ROW]
[ROW][C]10[/C][C]-0.116092[/C][C]-0.7156[/C][C]0.239294[/C][/ROW]
[ROW][C]11[/C][C]0.276605[/C][C]1.7051[/C][C]0.048169[/C][/ROW]
[ROW][C]12[/C][C]-0.069242[/C][C]-0.4268[/C][C]0.335954[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302675&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302675&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.613519	-3.782	0.000268
2	-0.291505	-1.797	0.040147
3	-0.204915	-1.2632	0.10711
4	0.102168	0.6298	0.266295
5	-0.180641	-1.1135	0.136234
6	-0.360207	-2.2205	0.016213
7	-0.067468	-0.4159	0.339912
8	-0.027854	-0.1717	0.43229
9	0.007649	0.0472	0.481319
10	-0.116092	-0.7156	0.239294
11	0.276605	1.7051	0.048169
12	-0.069242	-0.4268	0.335954

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ; par2 = -0.3 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 0 ; par10 = FALSE ;

Parameters (R input):

par1 = 12 ; par2 = -0.3 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;

R code (references can be found in the software module):

if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
x <- na.omit(x)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,'ACF(k)',header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,'PACF(k)',header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')

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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code